Machine Learning Engineer
$160K–$200K+ Offers For Graduates $160K–$200K+ Offers For Graduates 

3 weeks remote, 7 weeks onsite in Austin, TX
80–100 hours/week for 10 weeks
In-person
Short-term contract
full-time (90 hrs/week)

Machine Learning Engineer   $160K–$200K+ Offers For Graduates $160K–$200K+ Offers For Graduates 

Description

Gauntlet for America is a selective, fully funded 10-week fellowship program created to develop AI-native engineering talent for the United States government.

This is a high-intensity environment for proven engineers who seek to validate their ability to design, build, and maintain production-grade AI systems in settings where security, reliability, and tangible outcomes are critical.

Fellows deliver on a weekly cadence, undergo continuous evaluation, and work side by side with other top-tier engineers. After successful program completion, graduates transition into federal GS-12 engineering positions (~$150K + comprehensive federal benefits), contributing to systems that influence how the government functions.

The fellowship spans 10 weeks: the first 3 weeks are conducted remotely, followed by 7 weeks in person in Austin, Texas. Participants should anticipate a demanding schedule (80–100 hours per week) structured to accelerate learning, generate meaningful signal, and optimize career trajectory.

Program Outcomes:

  • 10+ production-ready AI systems delivered throughout the fellowship
  • Guaranteed placement into a federal engineering position (GS-12 equivalent, ~$160K–$200K+ based on experience + full benefits)
  • Contribution to high-impact systems that define how the U.S. government builds and deploys technology
  • Access to a professional network of AI-native engineers advancing public sector innovation

What you will be doing

  • Deliver production-ready AI applications weekly under firm deadlines
  • Develop systems using modern AI-first methodologies (agents, tool integration, evaluations, retrieval, deployment)
  • Engage in collaborative and competitive dynamics with elite engineering peers in a feedback-rich setting
  • Navigate real, unstructured problem domains comparable to those in government and enterprise contexts
  • Convert authentic project briefs into scoped, dependable, deployable solutions

Candidate requirements

  • U.S. citizenship is mandatory (no exceptions; background check will be conducted)
  • Proven engineering capability (both new graduates and experienced engineers are eligible)
  • Ability to relocate to Austin, TX for 7 weeks (full-time, on-site participation)
  • Ability to relocate to the Washington, DC area following program completion (remote work not available)
  • Robust problem-solving skills, rapid learning ability, and sound reasoning under pressure
  • Strong receptiveness to feedback and capacity to perform in high-intensity settings

Meet a successful candidate

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Fabiano Lucchese
Fabiano  |  SVP of Software Engineering
Brazil

Does your company encourage your natural creativity? This Brazilian engineering leader rediscovered his purpose after unleashing both his an...

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Applying for a role? Here’s what to expect.

Crossover's skill assessment process combines innovative AI power with decades of human research, to take the guesswork, human bias, and pointless filters out of recruiting high-performing teams.

Chat-style
screening interview.
STEP 1

Chat-style
screening interview.

Cognitive 
aptitude test.
STEP 2

Cognitive 
aptitude test.

Prove real-world 
job skills.
STEP 3

Prove real-world 
job skills.

Interview with the hiring manager.
STEP 4

Interview with the hiring manager.

Pass
proctored test.
STEP 5

Pass
proctored test.

Accept job offer.
STEP 6

Accept job offer.

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About Crossover

What you will learn

Phase 1: Remote (Weeks 1–3) — Foundations in AI-First Engineering

  • AI-first development workflows (coding agents, MCP, real-time collaboration)
  • Retrieval-Augmented Generation (RAG), embeddings, and vector databases
  • Rapid project sprints with a focus on delivery under constraints

Phase 2: On-Site in Austin (Weeks 4–10) — Scalable Production AI

  • Agent architectures, evaluations, verification, and observability (LangChain/LangSmith/LangFuse/CrewAI)
  • Enterprise-level delivery: quality assurance, reliability, and high-standard execution
  • Fine-tuning and deployment strategies (LoRA/QLoRA + production integration)
  • Multi-agent modernization applied to real-world codebases
  • Multimodal AI development (image/video/voice) and scalable cloud infrastructure (AWS/Azure)

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The Olympics of work

It’s super hard to qualify—extreme quality standards ensure every single team member is at the top of their game.

Premium pay for premium talent

Premium pay for premium talent

Over 50% of new hires double or triple their previous pay. Why? Because that’s what the best person in the world is worth.

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Shortlist by skills, not bias

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